This is the implementation of the paper Group-wise Correlation Stereo Network, CVPR 19, Xiaoyang Guo, Kai Yang, Wukui Yang, Xiaogang Wang, and Hongsheng Li [Arxiv]

• python 3.6
• Pytorch >= 0.4.1

Download Scene Flow Datasets, KITTI 2012, KITTI 2015

Scene Flow Datasets

run the script ./scripts/sceneflow.sh to train on Scene Flow datsets. Please update DATAPATH in the bash file as your training data path.

KITTI 2012 / 2015

run the script ./scripts/kitti12.sh and ./scripts/kitti15.sh to finetune on the KITTI 12/15 dataset. Please update DATAPATH and --loadckpt as your training data path and pretrained SceneFlow checkpoint file.

run the script ./scripts/kitti12_save.sh and ./scripts/kitti15_save.sh to save png predictions on the test set of the KITTI datasets to the folder ./predictions.

Scene Flow KITTI 2012/2015

If you find this code useful in your research, please cite:

@inproceedings{guo2019group,
  title={Group-wise Correlation Stereo Network},
  author={Guo, Xiaoyang and Yang, Kai and Yang, Wukui and Wang, Xiaogang and Li, Hongsheng},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3273--3282},
  year={2019}
}

Thanks to Jia-Ren Chang for opening source of his excellent work PSMNet. Our work is inspired by this work and part of codes in models are migrated from PSMNet.